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9th International Conference on Technology and Energy Management, ICTEM 2024

作者： Kiani, Hossein Golshaeian, Sajad Nazari, Mohammad Hassan Gharehpetian, G.B. Hosseinian, Seyed Hossein Sarbazi, Jafar Amirkabir University of Technology Department of Electrical Engineering Tehran Iran Smart Control Systems Department Tehran Iran

ISBN: (纸本)9798350329797

As the world's population grows, many nations grapple with the task of supplying sufficient energy. One effective way to manage and plan for this demand is through energy demand forecasting. In this research, we adopt a method employing machine learning algorithms to predict energy demand in various countries, both developed and developing, up to the year 2050. For our long-term forecast covering 2020 to 2050, two types of historical data are utilized: (i) energy consumption (EEC), and (ii) socio-economic indicators, such as Gross domestic product (GDP), energy import and export, and population. An Artificial Neural network (ANN) based machine learning is employed utilizing 30 years' worth of socio-economic data (1991-2020). In this manner, the utilization of the ANN facilitates the prediction of long-term energy consumption (EEC) for the planning period spanning from 2020 to 2050. Furthermore, we present an optimization model designed to enhance the precision of our predictions. The outcomes from machine learning algorithms serve as input for our comprehensive model, implemented through ANN across various sections. Ultimately, our forecasts indicate a projected increase in electric energy consumption by 130.1% for Iran, 37.4% for Portugal, and 58.6% for the United States in 2050 compared to 2020. Significant distinctions exist between developing and developed economies with regard to the anticipated trends in Energy Efficiency Compliance (EEC). © 2024 IEEE.

关键词： Adversarial machine learning

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Cooperative Output Regulation of Heterogeneous systems over Directed Graphs:A Dynamic Adaptive Event-Triggered Strategy

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Journal of systems Science & Complexity 2023年第3期36卷 909-921页

作者： SU Hang CHENG Bin LI Zhongkui State Key Laboratory for Turbulence and Complex Systems and Department of Mechanics and Engineering Science College of EngineeringPeking UniversityBeijing 100871China Department of Control Science and Engineering College of Electronics and Information EngineeringTongji UniversityShanghai 201804China Frontiers Science Center for Intelligent Autonomous Systems Shanghai 201210China

This paper investigates the cooperative output regulation problem of heterogeneous linear multi-agent systems over directed graphs with the constraint of communication *** that there exists an exosystem whose state information is not available to all agents,the authors develop distributed adaptive event-triggered observers for the followers based on relative information between neighboring *** should be pointed out that,two kinds of time-varying gains are introduced to avoid relying on any global information associated with the network,and dynamic triggering conditions are designed to get rid of continuous *** the basis of the designed observers,the authors devise a local controller for each *** with the existing related works,the main contribution of the current paper is that the cooperative output regulation problem for general directed graphs is solved requiring neither global information nor continuous communications.

关键词： Adaptive control consensus cooperative output regulation directed graph event-triggered control multi-agent systems

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Modified Covariance Intersection-Based Sensor Fault Tolerance of a Gas Turbine Engine

Modified Covariance Intersection-Based Sensor Fault Toleranc...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Chakraborty, Tirthankar Maity, Arnab Intelligent Systems and Control Lab Department of Aerospace Engineering Indian Institute of Technology Bombay Mumbai400076 India

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

Fault tolerance is crucial in the design and operation of gas turbine engines, where even minor malfunctions can disrupt operations and compromise performance. This paper presents a modified covariance intersection-based decentralized estimator which can ensure uninterrupted operation amidst sensor failures. A network of sensor nodes within the engine is considered. Each node in the network computes a local state estimate, which is subsequently fused with the other node estimates at each time instant. The developed algorithm uses a novel weight adaptation scheme to fuse the node estimates and the associated covariances. The node weights are expressed as a function of the covariance matrix of the node estimate and a scaling matrix. This algorithm is tested through simulation by injecting faults in the sensors of a small-scale gas turbine engine primarily used for research, called the SR-30 engine. The simulation results illustrate the effectiveness of the proposed estimator in ensuring the integrity of the state estimates in the presence of drift and bias faults in the sensors. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Gas turbines

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Real-time power flow analysis and management for a long-endurance solar UAV during continuous flight

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CEAS Aeronautical Journal 2023年第4期14卷 1035-1049页

作者： Ghelem, Nourddine Boudana, Djamel Bouchhida, Ouahid Laboratory of Process Control LCP Department of Engineering Control Systems and Applied Mathematics National Polytechnic School ENP of Algiers 10 St Hacen Badi El Harrach Algiers Algeria Department of Electrical Engineering LREA Laboratory University of Medea Medea Algeria

One of the primary challenges for Unmanned Aerial Vehicle (UAV) developers is to improve their endurance while in the air, as their typical flight time is limited to a few hours. One widely used technology to enhance their endurance is harnessing solar energy to power UAV and charge their batteries in flight. This article presents the development of a real-time simulation environment to enable the continuous flight of the Sky Sailor solar UAV. Through the utilization of a solar irradiance model, a solar panel model, real-time power generation is calculated. Simultaneously, the UAV’s full dynamic model, along with the autopilot and propulsion system model, is employed to determine the energy consumption at each moment. The energy management algorithm then compares the acquired energy with the power consumed, and in cases of surplus energy, it is efficiently stored in the battery for nighttime usage. Simulations show that continuous flight of the drone can be achieved during the summer season, when the daylight hours are long enough to fully charge the battery, With the ability to fly continuously during this period, the UAV can be used in various areas, such as monitoring forest fires, agricultural fields, beaches, and security monitoring for oil companies and their life bases in deserts. © 2023, Deutsches Zentrum für Luft- und Raumfahrt e.V.

关键词： Solar energy

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Pneumonia Detection from X-ray Images Using Convolutional Neural networks 24

Pneumonia Detection from X-ray Images Using Convolutional Ne...

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24th International Conference on control systems and Computer Science, CSCS 2023

作者： Dediu, Viorel Udrea, Andreea Faculty of Automatic Control and Computer Science Univesity Politehnica of Bucharest Department of Automatic Control and Systems Engineering Bucharest Romania

ISBN: (纸本)9798350313390

Pneumonia is one of the top causes of death in Romania and early detection of this disease improves the recovery chances and shortens the length of hospitalization. In this work, we develop a solution for automatic pneumonia detection based on convolutional neural networks. Four network models are investigated. They are trained on 4.163 images from a public dataset and tested on 530 images. The best results are obtained by one of the proposed models conducting to a sensitivity of 98.72%, an accuracy of 89.81%, and ROC 93.46%. Thus, this research proposes a lightweight screening tool that can help triaging the patients with pneumonia. © 2023 IEEE.

关键词： Convolution

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Robust design of sliding mode control for airship trajectory tracking with uncertainty and disturbance estimation

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Journal of systems engineering and Electronics 2024年第1期35卷 242-258页

作者： WASIM Muhammad ALI Ahsan CHOUDHRY Mohammad Ahmad SHAIKH Inam Ul Hasan SALEEM Faisal Department of Aeronautics and Astronautics Engineering Institute of Space TechnologyIslamabad 44000Pakistan Department of Electrical Engineering University of Engineering and TechnologyTaxila 47080Pakistan Department of Measurements and Control Systems Silesian University of TechnologyGliwice 44-101Poland The Joint Doctoral School Silesian University of TechnologyGliwice 44-100Poland

The robotic airship can provide a promising aerostatic platform for many potential *** applications require a precise autonomous trajectory tracking control for *** has a nonlinear and uncertain *** is prone to wind disturbances that offer a challenge for a trajectory tracking control *** paper addresses the airship trajectory tracking problem having time varying reference path.A lumped parameter estimation approach under model uncertainties and wind disturbances is opted against distributed *** uses extended Kalman filter(EKF)for uncertainty and disturbance *** estimated parameters are used by sliding mode controller(SMC)for ultimate control of airship trajectory *** comprehensive algorithm,EKF based SMC(ESMC),is used as a robust solution to track airship *** proposed estimator provides the estimates of wind disturbances as well as model uncertainty due to the mass matrix variations and aerodynamic model *** stability and convergence of the proposed method are investigated using the Lyapunov stability *** simulation results show that the proposed method efficiently tracks the desired *** method solves the stability,convergence,and chattering problem of SMC under model uncertainties and wind disturbances.

关键词： airship chattering extended Kalman filter(EKF) model uncertainties estimation sliding mode controller(SMC)

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Operation Optimization of Integrated Energy System Considering Demand Response and Carbon Trading 6

Operation Optimization of Integrated Energy System Consideri...

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6th International Conference on Power and Energy Technology, ICPET 2024

作者： Fan, Ruizhe Li, Xuecheng Li, Jun School of Electrical and Control Engineering North China University of Technology Beijing China Department of Automatic Control and Complex Systems University of Duisburg-Essen Duisburg Germany

ISBN: (纸本)9798350375855

Integrated energy system is a useful tool for achieving the"dual-carbon"goal. In order to explore the demand-side adjustable potential of the comprehensive energy system for lowering carbon emissions, this paper proposes an optimal operation model that accounts for demand response under a carbon trading mechanism. Initially, the demand response is classified into two categories based on the characteristics of the load response. Additionally, a carbon trading mechanism is built for the integrated energy system by allocating the carbon emission quotas for the system using the baseline technique, which is free of charge. The actual carbon emissions from the gas turbine and gas boiler are also taken into account. Ultimately, a low-carbon optimization operation model of the integrated energy system is established, with the goal of minimizing the total cost of energy purchase, carbon trading, and operation and maintenance. The suggested model's validity is then confirmed through four types of typical scenarios. © 2024 IEEE.

关键词： Demand response

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Frequency Domain Auto-tuning of Structured LPV controllers for High-Precision Motion control 63

Frequency Domain Auto-tuning of Structured LPV Controllers f...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Broens, Yorick Butler, Hans Toth, Roland Asml Veldhoven Netherlands Eindhoven University of Technology Department of Electrical Engineering Eindhoven Netherlands Hunren Institute for Computer Science and Control Systems and Control Laboratory Hungary

ISBN: (纸本)9798350316339

Motion systems are a vital part of many industrial processes. However, meeting the increasingly stringent demands of these systems, especially concerning precision and throughput, requires novel control design methods that can go beyond the capabilities of traditional solutions. Traditional control methods often struggle with the complexity and position-dependent effects inherent in modern motion systems, leading to compromises in performance and a laborious task of controller design. This paper addresses these challenges by introducing a novel structured feedback control auto-tuning approach for multiple-input multiple-output (MIMO) motion systems. By leveraging frequency response function (FRF) estimates and the linear-parameter-varying (LPV) control framework, the proposed approach automates the controller design, while providing local stability and performance guarantees. Key innovations include norm-based magnitude optimization of the sensitivity functions, an automated stability check through a novel extended factorized Nyquist criterion, a modular structured MIMO LPV controller parameterization, and a controller discretization approach which preserves the continuous-time (CT) controller parameterization. The proposed approach is validated through experiments using a state-of-the-art moving-magnet planar actuator prototype. © 2024 IEEE.

关键词： Continuous time systems

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Assessment of the Digital Measuring Transformers Application in Power Distribution Zone

Assessment of the Digital Measuring Transformers Application...

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2024 International Russian Automation Conference, RusAutoCon 2024

作者： Filatova, Galina Lebedev, Vladimir Tolstoukhov, Andrey Ivanovo State Power Engineering University Automatic control of electric power systems department Ivanovo Russia

Combined digital measuring current and voltage transformers (DCVTs), developed at Ivanovo State Power engineering University (ISPEU), are innovative products. The researchers have accumulated some operating experience of devices in existing electrical installations and experience in numerous laboratory tests. At the same time, a number of aspects of the DCVT use still remain the subject of research, for example, the functioning of DCVTs as a primary sensor for protection against single-phase ground faults (SPGFs). It is also necessary to evaluate the effect of the introduction of DCVTs in the overhead networks of power distribution zones (PDZs), primarily from the point of view of reducing the costs of searching for the location of the SPGFs. The procedure for searching for an electrical fault using the functions built into DCVT 6 -10 kV is described. The article describes the effects of the introduction of DCVTs in 6-10 kV distribution zones, and also provides criteria that allow us to assess in which cases the use of DCVTs and technologies based on them will be most beneficial. © 2024 IEEE.

关键词： Distribution transformers

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Real-Time Intrusion Detection Based on Decision Fusion in Industrial control systems

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical systems 2024年 2卷 143-153页

作者： Xue, Yawen Pan, Jie Geng, Yangyang Yang, Zeyu Liu, Mengxiang Deng, Ruilong Information Engineering University Zhengzhou450001 China Singapore University of Technology and Design ITrust 487372 Singapore The University of Sheffield Department of Automatic Control and Systems Engineering SheffieldS10 2TN United Kingdom Zhejiang University State Key Laboratory of Industrial Control Technology The College of Control Science and Engineering Hangzhou310027 China Huzhou Institute of Industrial Control Technology Huzhou313000 China

Industrial control systems (ICSs) are becoming increasingly interconnected as the rapid convergence of information technology (IT) and operation technology (OT) networks, and meanwhile massive attack surfaces have been exposed. However, traditional intrusion detection systems (IDSs) are difficult to be directly deployed in ICSs due to the hard real-time requirement and rare patching chance. Besides, the design of effective and practical IDSs is hampered by the lack of benchmarking ICS cybersecurity datasets. To bridge the gaps, this paper makes the first attempt by open-sourcing the developed ICS cybersecurity datasets and proposing a decision fusion based real-time IDS. Firstly, we design a customized cybersecurity dataset in a full-hardware and high-fidelity platform, including 7 types of cyber threats tailored for ICSs. The collected dataset includes network traffic, sensor readings, actuator status, and system parameters, providing the state-of-the-art benchmark dataset for ICSs consisting of cross-layer characteristics. Furthermore, we design an online decision fusion-based IDS by strategically integrating 4 widely-used machine learning models. The proposed IDS is deployed on a real-time running ethanol distillation, surpassing the performance of single detection models in terms of precision and F1-score, which substantially enhances intrusion detection accuracy and cybersecurity of ICS. © 2023 IEEE.

关键词： Intrusion detection

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